Rock mass structural surface undulation degree identification and evaluation method based on three-dimensional laser scanning

Abstract

The invention provides a rock mass structural surface fluctuation degree identification and evaluation method based on three-dimensional laser scanning, and the method comprises the following steps: S1, carrying out the three-dimensional laser scanning of a set rock mass measurement range through a three-dimensional laser scanner, and obtaining the point cloud of a rock mass in a designated region; s2, preprocessing the point clouds to obtain a point cloud set, screening boundary point clouds from the point cloud set, and fitting a structural surface by using the boundary point clouds; s3, calculating and marking the undulation degree of each structural surface; and S4, evaluating the stability of the rock mass according to the undulation degree of each structural surface. According to the method, the stability degree of the rock mass can be further determined by judging the rock mass structural surface, the fluctuation condition of the structural surface and the feature recognition efficiency of the rock mass structural surface.

Description

Technical Field

[0001] The invention relates to a rock mass structure recognition method, belonging to the technical field of rock mass structure surface feature recognition, and in particular to a rock mass structure surface fluctuation recognition and evaluation method based on three-dimensional laser scanning. Background Art

[0002] The rock mass encountered in geotechnical engineering is composed of structural surfaces and rock blocks. The development characteristics of the structural surface are very important factors that determine the physical and mechanical characteristics of the rock mass, especially the fluctuation of the structural surface, which is an important input parameter for determining the shear strength of the structural surface, and has an important influence on determining the permeability and deformation characteristics of the rock mass. Since the development scale of the structural surface varies, and the fluctuation of the structural surface is relatively random, the local area measured manually is likely to be unrepresentative, and the efficiency of manually measuring each structural surface one by one is also extremely low.

[0003] As an emerging surveying and mapping technology, 3D laser scanning has been widely used in terrain surveying and deformation monitoring and other fields. It can obtain 3D coordinate information by non-contact scanning of the point cloud on the surface of the object, restore the measured object, and scan within the horizontal range of 360° and the vertical range of 270°, which improves the shortcomings of traditional measurement methods and significantly improves the efficiency of feature recognition of rock structure surfaces. Therefore, it is very necessary to propose a method for identifying and evaluating the fluctuation of rock structure surfaces based on 3D laser scanning, identify the structural surface of the rock mass and its local characteristics, and facilitate further judgment of the stability of the rock structure. Summary of the invention

[0004] The purpose of the present invention is to overcome the above-mentioned defects and problems existing in the prior art, and to provide a method for identifying and evaluating the undulation of rock structural surfaces based on three-dimensional laser scanning, which uses rock point clouds to construct structural surfaces and grow them, thereby determining abnormal point clouds inside and outside the structural surface, and further analyzing the degree of concavity and convexity.

[0005] To achieve the above objectives, the technical solution of the present invention is: a method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning, comprising:

[0006] S1. Use a 3D laser scanner to perform 3D laser scanning on a set rock mass measurement range to obtain a point cloud of the rock mass in a specified area;

[0007] S2, preprocessing the point cloud to obtain a point cloud set; screening the boundary point cloud from the point cloud set, and fitting the structural surface using the boundary point cloud;

[0008] S3. Calculate and mark the undulation of each structural surface;

[0009] S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

[0010] On the basis of the above technical solution, preferably, in the step S1, when performing three-dimensional laser scanning, an odd number of measuring points are arranged along the horizontal extension direction of the set rock mass, the distance between adjacent measuring points does not exceed 1 / 3 of the maximum scanning distance of the three-dimensional laser scanner, and the point clouds obtained by adjacent measuring points for the same rock mass overlap by more than 15%, and targets are set in the scanning area where the point clouds overlap.

[0011] Preferably, in step S2, preprocessing the point cloud to obtain a point cloud set specifically includes:

[0012] De-noise the acquired point cloud; after eliminating the noise points, fuse the point clouds of each measuring point according to the posture of the target in the overlapping area of ​​the point clouds; set the distance between adjacent point clouds in the fused point cloud to 5mm and resample; all the point clouds after resampling are the point cloud set; transfer each point cloud in the point cloud set to the world coordinate system to obtain the real three-dimensional coordinates.

[0013] Further preferably, in step S2, the step of selecting a boundary point cloud from the point cloud set and fitting the structural surface using the boundary point cloud specifically includes:

[0014] S21, selecting a point cloud P from the point cloud set as a center point, and obtaining a first neighborhood point set in a circular neighborhood with a preset radius and the center point as the circle center;

[0015] S22, constructing a covariance matrix C based on the principal components of the first neighborhood point set, obtaining eigenvalues ​​of the covariance matrix C, and determining the curvature of the first neighborhood point set based on the eigenvalues;

[0016] If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed;

[0017] If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the position of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed as a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed;

[0018] S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is:

[0019] v1x+v2y+v3z+d=0;

[0020] v = (v1, v2, v3);

[0021] Where: v = (v1, v2, v3) is the normal vector of the fitting plane, x, y, z are the three-dimensional coordinate axes, and d is the distance from the fitting plane to the origin of the world coordinate system;

[0022] S24, taking any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtaining a second neighborhood point set again within a circular neighborhood of a preset radius of the new center point, and recalculating the curvature of the second neighborhood point set and the normal vector of the fitting plane according to the method of step S22 and step S23, and determining the curvature of the second neighborhood point set;

[0023] If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold;

[0024] If it does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set;

[0025] If the angle exceeds the first angle threshold, the point cloud in the second neighborhood point set is saved separately as a new structural surface;

[0026] Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold;

[0027] If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained;

[0028] If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed;

[0029] If the curvature of the second neighborhood point set is not less than the curvature threshold, the position of the point cloud causing the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, the second neighborhood point set is re-acquired, and step S24 is executed again;

[0030] S25. Repeat steps S21-S24 until all the non-marked abnormal point clouds in the point cloud set are fitted as structural surfaces.

[0031] More preferably, the step S22 specifically includes:

[0032] The covariance matrix is ​​constructed as:

[0033]

[0034] Where: pi is a point in the first neighborhood point set, i=1, 2, 3, ..., n;

[0035] Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalue λ and eigenvector V, λV=CV, eigenvalue λ=(λ1,λ2,λ3), λ1≥λ2≥λ3, eigenvector V=(V1,V2,V3);

[0036] Set the curvature s as follows:

[0037]

[0038] The curvature threshold is 0.15.

[0039] Further preferably, in step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations where the point clouds causing regional anomalies appear to construct the first abnormal point cloud set specifically refers to:

[0040] Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and number the point clouds in the neighborhood point set in sequence according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, eliminate several point clouds in the first neighborhood point set with point cloud numbers from large to small; if after eliminating several point clouds, the curvature of the recalculated first neighborhood point set is still less than the curvature threshold, the eliminated point clouds are marked as the first abnormal point clouds and added to the first abnormal point cloud set.

[0041] Preferably, the first angle threshold is 3°; the second angle threshold is 10°.

[0042] Further preferably, the step S3 specifically includes:

[0043] S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface;

[0044] If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set;

[0045] If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass;

[0046] S32, determining that there is a depression or a bulge on the structural surface with the second abnormal point cloud;

[0047] S33, for a structural surface that is identified as having a depression or a protrusion, obtain the trace of the structural surface, and draw a number of virtual line segments parallel to the trace, so that the virtual line segments pass through the second abnormal point cloud and its vicinity, and draw contour lines that deviate from the structural surface according to the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with the spacing between adjacent contour lines being equal; obtain the distance of the contour line that deviates farthest from the structural surface;

[0048] S34, obtaining a first area of ​​a region enclosed by a contour line closest to the structural surface, and using a ratio of the first area to a projected area of ​​the structural surface to measure the undulation of the structural surface.

[0049] More preferably, the step S34 specifically includes:

[0050] A straight line is used to fit the vertices of the contour lines closest to the structural surface, and a virtual circumscribed circle is constructed so that the contour of the virtual circumscribed circle has the most vertices of the contour lines; the first area is calculated by the following formula:

[0051]

[0052] Where: r is the radius of the virtual circumscribed circle, k1 and k2 are adjustment coefficients, x1 is the number of contour vertices intersecting the outline of the virtual circumscribed circle, and x2 is the number of contour vertices located inside the virtual circumscribed circle;

[0053] Assuming that the projection area of ​​the structural surface is S0, the ratio of the first area to the projection area of ​​the structural surface S1 / S0 is used as the undulation of the structural surface.

[0054] More preferably, the step S4 specifically includes:

[0055] After obtaining the fluctuation S1 / S0 of the structural surface and the distance h of the contour line farthest from the structural surface, the stability of the rock mass is judged according to the following situations:

[0056] The first type: if the ratio of the undulation S1 / S0 does not exceed 10%, the stability of the rock mass is considered to be level 1;

[0057] The second type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line in the area enclosed by the contour line closest to the structural surface and the length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2;

[0058] The third type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, then the angle between the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S hThe rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h>25, the stability of the rock mass is considered to be level 3;

[0059] The fourth type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line between vertices in the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, the first area of ​​the area enclosed by the contour line closest to the structural surface is equal to the area S h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h≤25, the stability of the rock mass is considered to be level 4;

[0060] The stability of the rock mass is arranged from the highest to the worst, namely, level 4, level 3, level 2, and level 1.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] 1. In the method for identifying and evaluating the undulation of rock structure surface based on three-dimensional laser scanning of the present invention, the rock structure surface can be quickly acquired, and the undulations or depressions that may exist on the surface of the structure surface can be identified from the fitting and growth process of the structure surface, thereby further identifying the stability state of the rock mass, and automatically and quickly identifying environmental risk factors, which has a good auxiliary significance for engineering construction and disaster prevention.

[0063] 2. In the rock mass structural surface fluctuation identification and evaluation method based on three-dimensional laser scanning of the present invention, whether the structural surface is stable and the stability classification can be quickly evaluated according to the set value range. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0065] Figure 1 The present invention is a flowchart of the steps of a method for identifying and evaluating the undulation of a rock structure surface based on three-dimensional laser scanning. DETAILED DESCRIPTION

[0066] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Embodiment 1:

[0068] like Figure 1 As shown, the present invention provides a method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning, comprising the following steps:

[0069] S1. Use a 3D laser scanner to perform 3D laser scanning on a set rock mass measurement range to obtain a point cloud of the rock mass in a specified area;

[0070] When performing 3D laser scanning, an odd number of measuring points are arranged along the horizontal extension direction of the set rock mass. The distance between adjacent measuring points does not exceed 1 / 3 of the maximum scanning distance of the 3D laser scanner, and the point clouds obtained by adjacent measuring points for the same rock mass overlap by more than 15%. Targets are set in the scanning area where the point clouds overlap. Setting a certain distance and ensuring that the point clouds overlap each other is to ensure the accuracy of the point cloud and provide a basis for the accuracy of the subsequent splicing of point clouds from different measuring points. During actual measurement, for rock masses that may have blind spots in the field of vision, the density of local measurements can be increased to obtain point clouds of the same rock mass from multiple angles.

[0071] S2, preprocessing the point cloud to obtain a point cloud set; screening the boundary point cloud from the point cloud set, and fitting the structural surface using the boundary point cloud;

[0072] This step includes two aspects. The first is the point cloud preprocessing process, which is to denoise the acquired point cloud. After eliminating the noise points, the point clouds of each measuring point are fused according to the posture of the target in the overlapping area of ​​the point cloud. The distance between adjacent point clouds in the fused point cloud is set to 5mm, and resampling is performed. All the point clouds after resampling are the point cloud set. Each point cloud in the point cloud set is transferred to the world coordinate system to obtain the real three-dimensional coordinates.

[0073] Usually, in order to obtain higher-precision rock mass point clouds, a more refined scanning mode is selected. The scale of point cloud data obtained in this way is huge. It takes more than ten minutes to scan a point to obtain millions of point clouds. In order to improve the efficiency of subsequent data processing, resampling operations are used to reduce the point cloud density, which can significantly reduce the total number of point clouds. Point clouds that do not belong to rock masses can be manually deleted.

[0074] Then, the point cloud set is used to filter the boundary point cloud from the point cloud set, and the boundary point cloud is used to fit the structural surface, which specifically includes the following contents:

[0075] S21, selecting a point cloud p from the point cloud set as a center point, and obtaining a first neighborhood point set in a circular neighborhood with a preset radius and the center point as the circle center;

[0076] S22, constructing a covariance matrix C based on the principal components of the first neighborhood point set, obtaining eigenvalues ​​of the covariance matrix C, and determining the curvature of the first neighborhood point set based on the eigenvalues;

[0077] To determine the curvature of the first neighborhood point set based on the eigenvalue, the following is performed:

[0078] The covariance matrix is ​​constructed as:

[0079]

[0080] Where: p i is a point in the first neighborhood point set, i=1, 2, 3, ..., n;

[0081] Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalue λ and eigenvector V, λV=CV, eigenvalue λ=(λ1,λ2,λ3), λ1≥λ2≥λ3, eigenvector V=(V1,V2,V3);

[0082] Set the curvature s as follows:

[0083]

[0084] The curvature threshold is 0.15.

[0085] If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed;

[0086] If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the position of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed as a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed;

[0087] Here, the position of the center point can be adjusted by moving the unit point cloud away from the first abnormal point cloud by an integer multiple of the density, or by reducing the radius of the current circular neighborhood by a step of 5% of the preset radius without changing the current center point position, such as reducing the preset radius by 5% for the first time, reducing the preset radius by 10% for the second time, and so on, until the curvature threshold requirement is met.

[0088] In step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations where the point clouds causing regional anomalies appear to construct the first abnormal point cloud set specifically refers to:

[0089] Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and number the point clouds in the neighborhood point set in sequence according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, eliminate several point clouds in the first neighborhood point set with point cloud numbers from large to small; if after eliminating several point clouds, the curvature of the recalculated first neighborhood point set is still less than the curvature threshold, the eliminated point clouds are marked as the first abnormal point clouds and added to the first abnormal point cloud set.

[0090] For example, for a point cloud with n sequential numbers, first check one by one in the order of the nth, n-1th, and n-2th. If the curvature calculation result after one round of checking is not ideal, start the second round of checking. At this time, the second round of checking is performed according to the nth point cloud + n-1th point cloud, n-1th point cloud + n-2th point cloud, and so on. That is, 2 point clouds are eliminated each time, and one point cloud is repeatedly eliminated, and this process is repeated until the neighborhood point cloud that meets the requirements is screened, and the eliminated first abnormal point cloud is added to the first abnormal point cloud set.

[0091] S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is:

[0092] v1x+v2y+v3z+d=0;

[0093] v = (v1, v2, v3);

[0094] Where: v = (v1, v2, v3) is the normal vector of the fitting plane, x, y, z are the three-dimensional coordinate axes, and d is the distance from the fitting plane to the origin of the world coordinate system;

[0095] S24, taking any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtaining a second neighborhood point set again within a circular neighborhood of a preset radius of the new center point, and recalculating the curvature of the second neighborhood point set and the normal vector of the fitting plane according to the method of step S22 and step S23, and determining the curvature of the second neighborhood point set;

[0096] If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold;

[0097] If the angle does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set to achieve the expansion of the structural surface corresponding to the first neighborhood point set;

[0098] If the angle exceeds the first angle threshold, the point cloud in the second neighborhood point set is saved separately as a new structural surface; this step realizes the process of growing an existing structural surface or generating a new structural surface.

[0099] Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold;

[0100] If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained;

[0101] If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed;

[0102] If the curvature of the second neighborhood point set is not less than the curvature threshold, the position of the point cloud causing the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, the second neighborhood point set is re-acquired, and step S24 is executed again;

[0103] In this embodiment, the first angle threshold is set to 3°, and the second angle threshold is set to 10°. The second abnormal point cloud is a point cloud whose normal vector is obviously different from other point clouds of the structural surface.

[0104] The point cloud that causes the curvature anomaly has a specific curvature, which is obviously inconsistent with the curvature of other point clouds and needs further judgment, so it is marked and saved.

[0105] S25. Repeat steps S21-S24 until all the non-marked abnormal point clouds in the point cloud set are fitted as structural surfaces.

[0106] S3. Calculate and mark the undulation of each structural surface;

[0107] The specific contents of this step are:

[0108] S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface;

[0109] If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set;

[0110] If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass;

[0111] The first abnormal point cloud belonging to the structural surface will be removed from the first abnormal point cloud set until the remaining point clouds are all boundaries of the rock mass, and the boundary of the rock mass defines the limit position of the growth direction of the structural surface.

[0112] S32, determining that there is a depression or a bulge on the structural surface with the second abnormal point cloud;

[0113] S33, for a structural surface that is identified as having a depression or a protrusion, obtain the trace of the structural surface, and draw a number of virtual line segments parallel to the trace, so that the virtual line segments pass through the second abnormal point cloud and its vicinity, and draw contour lines that deviate from the structural surface according to the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with the spacing between adjacent contour lines being equal; obtain the distance of the contour line that deviates farthest from the structural surface;

[0114] The trace is a key element of the structural surface. The endpoints of the trace determine the edge feature positions of the structural surface and correspond to the maximum extension range of the structural surface. The trace is contained in the structural surface. The trace is a three-dimensional line, but since the three-dimensional coordinates of each point cloud including the second abnormal point cloud in the world coordinate system are known, the relative position relationship between the second abnormal point cloud and the trace is easy to obtain, and the contour line can reflect the shape characteristics of the convex or concave parts.

[0115] S34, obtaining a first area of ​​a region enclosed by a contour line closest to the structural surface, and using a ratio of the first area to a projected area of ​​the structural surface to measure the undulation of the structural surface.

[0116] The step S34 specifically includes:

[0117] A straight line is used to fit the vertices of the contour lines closest to the structural surface, and a virtual circumscribed circle is constructed so that the contour of the virtual circumscribed circle has the most vertices of the contour lines; the first area is calculated by the following formula:

[0118]

[0119] Where: r is the radius of the virtual circumscribed circle, k1 and k2 are adjustment coefficients, x1 is the number of contour vertices intersecting the outline of the virtual circumscribed circle, and x2 is the number of contour vertices located inside the virtual circumscribed circle;

[0120] Assuming that the projection area of ​​the structural surface is S0, the ratio of the first area to the projection area of ​​the structural surface S1 / S0 is used as the undulation of the structural surface.

[0121] S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

[0122] The step S4 specifically includes:

[0123] After obtaining the fluctuation S1 / S0 of the structural surface and the distance h of the contour line farthest from the structural surface, the stability of the rock mass is judged according to the following situations:

[0124] The first type: if the ratio of the undulation S1 / S0 does not exceed 10%, the stability of the rock mass is considered to be level 1;

[0125] The second type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line in the area enclosed by the contour line closest to the structural surface and the length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2;

[0126] The third type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, then the angle between the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h>25, the stability of the rock mass is considered to be level 3;

[0127] The fourth type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line between vertices in the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, the first area of ​​the area enclosed by the contour line closest to the structural surface is equal to the area S h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h≤25, the stability of the rock mass is considered to be level 4;

[0128] The stability of the rock mass is arranged from the highest to the worst, namely, level 4, level 3, level 2, and level 1.

[0129] Although the embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning, characterized in that: include: S1. Use a 3D laser scanner to perform 3D laser scanning on a set rock mass measurement range to obtain a point cloud of the rock mass in a specified area; S2, preprocessing the point cloud to obtain a point cloud set; screening the boundary point cloud from the point cloud set, and fitting the structural surface using the boundary point cloud; S3. Calculate and mark the undulation of each structural surface; S4. Evaluate the stability of the rock mass based on the undulation of the structural surface.

2. The method for identifying and evaluating the undulation of rock mass structural surfaces based on three-dimensional laser scanning according to claim 1 is characterized in that: In the step S1, when performing three-dimensional laser scanning, an odd number of measuring points are arranged along the horizontal extension direction of the set rock mass, the distance between adjacent measuring points does not exceed 1 / 3 of the maximum scanning distance of the three-dimensional laser scanner, and the point clouds obtained by adjacent measuring points for the same rock mass overlap by more than 15%, and targets are set in the scanning area where the point clouds overlap.

3. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 2 is characterized in that: In step S2, the point cloud is preprocessed to obtain a point cloud set, which specifically includes: De-noise the acquired point cloud; after eliminating the noise points, fuse the point clouds of each measuring point according to the posture of the target in the overlapping area of ​​the point clouds; set the distance between adjacent point clouds in the fused point cloud to 5mm and resample; all the point clouds after resampling are the point cloud set; transfer each point cloud in the point cloud set to the world coordinate system to obtain the real three-dimensional coordinates.

4. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 2 is characterized in that: In the step S2, the step of selecting the boundary point cloud from the point cloud set and fitting the structural surface using the boundary point cloud specifically includes: S21, selecting a point cloud p from the point cloud set as a center point, and obtaining a first neighborhood point set in a circular neighborhood with a preset radius and the center point as the circle center; S22, constructing a covariance matrix C based on the principal components of the first neighborhood point set, obtaining eigenvalues ​​of the covariance matrix C, and determining the curvature of the first neighborhood point set based on the eigenvalues; If the curvature of the first neighborhood point set is less than the curvature threshold, it indicates that the point clouds of the first neighborhood point set are located in the same plane, and step S23 is executed; If the curvature of the first neighborhood point set is not less than the curvature threshold, the point clouds of the first neighborhood point set are checked one by one and the position of the point cloud causing the regional abnormality is marked as the first abnormal point cloud, and several first abnormal point clouds are constructed as a first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, and step S22 is re-executed; S23, performing plane fitting of the first neighborhood point set, and taking the plane fitted by the first neighborhood point set as a structural surface; the expression of the fitted plane is: v1x+v2y+v3z+d=0; v=(v1,v2,v3); Where: v = (v1, v2, v3) is the normal vector of the fitting plane, x, y, z are the three-dimensional coordinate axes, and d is the distance from the fitting plane to the origin of the world coordinate system; S24, taking any point cloud outside the boundary of the circular area where the first neighborhood point set is located as a new center point, obtaining a second neighborhood point set again within a circular neighborhood of a preset radius of the new center point, and recalculating the curvature of the second neighborhood point set and the normal vector of the fitting plane according to the method of step S22 and step S23, and determining the curvature of the second neighborhood point set; If the curvature of the second neighborhood point set is less than the curvature threshold, the point cloud of the second neighborhood point set is deemed to be coplanar, and it is further determined whether the angle deviation between the normal vector of the fitting plane of the second neighborhood point set and the normal vector of the fitting plane of the first neighborhood point set exceeds the first angle threshold; If it does not exceed the first angle threshold, the point cloud of the second neighborhood point set is added to the first neighborhood point set; If the angle exceeds the first angle threshold, the point cloud in the second neighborhood point set is saved separately as a new structural surface; Calculate the normal vector for each point cloud located on the same structural surface and set the second angle threshold; If the angle between the normal vector of the point cloud and the normal vector of the structural surface does not exceed the second angle threshold, the point cloud is retained; If the angle between the normal vector of the point cloud and the normal vector of the structural surface exceeds the second angle threshold, the abnormal point cloud is removed from the neighborhood point set corresponding to the current structural surface, marked and saved as a second abnormal point cloud, and a second abnormal point cloud set containing several second abnormal point clouds is constructed; If the curvature of the second neighborhood point set is not less than the curvature threshold, the position of the point cloud causing the regional anomaly is marked, and the point cloud is added to the first abnormal point cloud set, the position of the center point is adjusted or the preset radius is reduced, the second neighborhood point set is re-acquired, and step S24 is executed again; S25. Repeat steps S21-S24 until all the non-marked abnormal point clouds in the point cloud set are fitted as structural surfaces.

5. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 4 is characterized in that: The step S22 specifically includes: The covariance matrix is ​​constructed as: Where: p i is a point in the first neighborhood point set, i=1, 2, 3, ..., n; Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalue λ and eigenvector V, λV=CV, eigenvalue λ=(λ1,λ2,λ3), λ1≥λ2≥λ3, eigenvector V=(V1,V2,V3); Set the curvature s as follows: The curvature threshold is 0.

15.

6. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 5 is characterized in that: In step S22, the step of checking the point clouds of the first neighborhood point set one by one and marking the locations of the point clouds causing regional anomalies to construct the first abnormal point cloud set specifically refers to: Specify a reference direction, traverse the point cloud in the circular neighborhood of the center point in a clockwise direction, and number the point clouds in the neighborhood point set in sequence according to the angle with the reference direction; when the curvature of the first neighborhood point set is not less than the curvature threshold, remove several point clouds in the first neighborhood point set with point cloud numbers from large to small; If after removing several point clouds, the curvature of the recalculated first neighborhood point set is still less than the curvature threshold, the several removed point clouds are marked as first abnormal point clouds and added to the first abnormal point cloud set.

7. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 6, characterized in that: The first angle threshold is 3°; the second angle threshold is 10°.

8. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 5, characterized in that: The step S3 specifically includes: S31, identifying the point cloud in the first abnormal point cloud set, that is, identifying whether the point cloud in the first abnormal point cloud set belongs to any structural surface; If it belongs to any structural surface, the point cloud is removed from the first abnormal point cloud set; If it does not belong to any structural surface, the first abnormal point cloud is considered to belong to the boundary of the rock mass; S32, determining that there is a depression or a protrusion on the structural surface with the second abnormal point cloud; S33, for a structural surface that is identified as having a depression or a protrusion, obtain the trace of the structural surface, and draw a number of virtual line segments parallel to the trace, so that the virtual line segments pass through the second abnormal point cloud and its vicinity, and draw contour lines that deviate from the structural surface according to the distance between the real three-dimensional coordinates of each point cloud on the virtual line segment and the structural surface, with the spacing between adjacent contour lines being equal; obtain the distance of the contour line that deviates farthest from the structural surface; S34, obtaining a first area of ​​a region enclosed by a contour line closest to the structural surface, and using a ratio of the first area to a projected area of ​​the structural surface to measure the undulation of the structural surface.

9. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 8, characterized in that: The step S34 specifically includes: A straight line is used to fit the vertices of the contour lines closest to the structural surface, and a virtual circumscribed circle is constructed so that the contour of the virtual circumscribed circle has the most vertices of the contour lines; the first area is calculated by the following formula: Where: r is the radius of the virtual circumscribed circle, k1 and k2 are adjustment coefficients, x1 is the number of contour vertices intersecting the outline of the virtual circumscribed circle, and x2 is the number of contour vertices located inside the virtual circumscribed circle; Assuming that the projection area of ​​the structural surface is S0, the ratio of the first area to the projection area of ​​the structural surface S1 / S0 is used as the undulation of the structural surface.

10. The method for identifying and evaluating the undulation of rock mass structural surface based on three-dimensional laser scanning according to claim 9, characterized in that: The step S4 specifically includes: After obtaining the fluctuation S1 / S0 of the structural surface and the distance h of the contour line farthest from the structural surface, the stability of the rock mass is judged according to the following situations: The first type: if the ratio of the undulation S1 / S0 does not exceed 10%, the stability of the rock mass is considered to be level 1; The second type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line in the area enclosed by the contour line closest to the structural surface and the length of the structural surface is greater than 30°, the stability of the rock mass is considered to be level 2; The third type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest vertex line of the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, then the angle between the first area of ​​the area enclosed by the contour line closest to the structural surface and the area S h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h>25, the stability of the rock mass is considered to be level 3; The fourth type: if the ratio of the undulation S1 / S0 exceeds 10%, and the angle between the longest line between vertices in the area enclosed by the contour line closest to the structural surface and the length of the structural surface does not exceed 30°, and the first area of ​​the area enclosed by the contour line closest to the structural surface and the area enclosed by the contour line farthest from the structural surface are equal to each other, the first area of ​​the area enclosed by the contour line closest to the structural surface is equal to the area S h The rate of change of the difference with the distance from the contour line farthest from the structural surface (S1-S h ) / h≤25, the stability of the rock mass is considered to be level 4; The stability of the rock mass is arranged from the highest to the worst, namely, level 4, level 3, level 2, and level 1.

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